{"id":"W2114387920","doi":"10.1139/f00-221","title":"The influence of stock structure and environmental conditions on the recruitment process of Baltic cod estimated using a generalized additive model","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Abiotic component; Stock (firearms); Ecology; Biology; Stock assessment; Baltic sea; Biotic component; Density dependence; Fishery; Population; Environment variable; Environmental science; Geography; Fishing; Oceanography; Demography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002867689,0.0006513151,0.0007849812,0.0006341744,0.0004111535,0.000928105,0.0007453567,0.000550799,0.0009160081],"category_scores_gemma":[0.005324214,0.0005488534,0.0011656,0.0005913179,0.0006024658,0.0004323985,0.0006523171,0.0005194524,0.0001670504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005773976,"about_ca_system_score_gemma":0.000956956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03658056,"about_ca_topic_score_gemma":0.03952329,"domain_scores_codex":[0.9989249,0.0005435731,0.00005728568,0.0002799951,0.00006597063,0.0001282686],"domain_scores_gemma":[0.9981883,0.001270267,0.0001963283,0.0001218513,0.0001453095,0.00007794341],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005583717,0.0002690066,0.3944563,0.000107574,0.0009825035,0.0006789555,0.000495726,0.5497362,0.006401521,0.004134363,0.0006361525,0.0415433],"study_design_scores_gemma":[0.00003269141,0.0001627985,0.09890915,0.00001483155,0.0002547891,0.0001023857,0.00007334155,0.8983931,0.0004096312,0.001348037,0.0002685261,0.00003074159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774837,0.000101122,0.02169601,0.00007830786,0.00001422943,0.00001879711,0.000121213,0.00008376015,0.0004028397],"genre_scores_gemma":[0.9937762,0.00006826535,0.005309189,0.00001807124,0.000006511635,0.0000283452,0.0001588771,0.00001039631,0.0006241208],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03658056,"threshold_uncertainty_score":0.07273531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.046381909889589,"score_gpt":0.2818537776215706,"score_spread":0.2354718677319816,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}